A thesis 2019
Water resources have become scarce in most tropical areas of Tanzania due to climate
change. Any changes to the hydrological cycle may have significant effects on the water
resources in the river basins of Tanzania. The impact of climate change on water resources
in Tanzania have been studied using General Circulation Models (GCM) which run at low
spatial resolutions of 100-300 km. The resolution is too coarse to provide useful
information about climate change impact in small catchments as many physical processes
which control local climate e.g.; vegetation, hydrology, topography is not fully
parameterized and hence results on uncertainty in model prediction.
The main aim of this research was to quantify the uncertainty in model predictions for the
Mbarali River Sub-catchment of the Upper Great Ruaha River Sub-basin in the Rufiji
River Basin, Tanzania. Three research objectives were analyzed; the first objective was to
evaluate the performance of the Coordinated Regional Downscaling Experiment Regional
Climate Model (CORDEX, Regional Climate Models) in simulating rainfall
characteristics of the Mbarali River Sub catchment. The area weighted average method
was used to calculate the average rainfall from the CORDEX RCMs and from
ERA-Interim reanalysis over the entire Mbarali River sub-catchment. Comparison
between rainfall data from CORDEX RCMs and ERA-Interim reanalysis was done to test
the ability of the CORDEX RCMs to reproduce the annual cycles, interannual variability,
annual total and trends of rainfall as presented by the ERA-Interim reanalysis.
The second objective assessed the impact of climate change on hydrological
characteristics using the Soil and Water Assessment Tool (SWAT) model. The ability of
the SWAT model to simulate catchment processes was assessed through a calibration and validation process, which was a key factor in reducing uncertainty and increasing user
confidence in its predictive abilities. The SWAT model was driven by high resolution
climate simulations for historical climate condition (1971-2000) as well as future climate
projections (2011-2040, 2041-2070 and 2071-2100) for two Representative concentration
Pathways (RCPs): RCP 4.5 and RCP 8.5. Furthermore, Ensemble of RCMs was applied
into SWAT to simulate water resources availability and the results were compared with
individual models (HIRHAM5, CCLM4, RACMO22T, RCA4). The Rainfall and
Temperature data were obtained from the selected four CORDEX RCMs driven by three
different General Circulation Models (GCMs). Inverse Distance Weight Average (IDWA)
was used to interpolate model gridded climate simulation to the location of weather
station. The third objective assessed the impacts of land use and land cover change on the
hydrology using integration of remote sensing data, QGIS and SWAT model. The land
use and land cover (LULC) maps for three window period snapshots, 1990, 2006 and
2017 were created from Landsat TM and OLI_TIRS. Supervised classification was used
to generate LULC maps using the Maximum Likelihood Algorithm and Kappa statistics
for assessment of accuracy.
The findings of the first objective are that CORDEX RCMs were able to capture well the
seasonal and annual cycles of rainfall. However, they underestimated the amount of
rainfall in March, April and May (MAM) and overestimated in October, November and
December (OND) respectively. CORDEX RCMs reproduce interannual variation of
rainfall. The source of uncertainties was revealed when the same RCMs driven by
different GCMs and when different RCMs driven by the same GCM in simulating
rainfall. It was found that the error and biases from RCMs and driving GCMs contribute
roughly equally. Overall, the evaluation found reasonable (although variable) model
capability in representing the mean climate, interannual variability and rainfall trends.The results suggest that CORDEX RCM is suitable in simulating rainfall, maximum
temperature and minimum temperature.
The findings of the second objective showed that SWAT model simulated stream flow
and water balance components differently when two different RCMs were forced by the
same GCMs as well as when the same RCMs were forced by different GCMs. The
differences are related to the formulation of the RCMs themselves. For example,
RACMO22T and HIRHAM5 driven with the same GCM (ICHEC-EARTH) simulate
different amount of stream flows, surface runoff, water yield and groundwater yield in
historical (1971–2000) as well as in present century (2011-2040), mid-century (2041-
2070) and end century (2071-2100). Ensemble RCMs projected decrease in stream flows
by 13.67% under RCP 8.5. However annual rainfall was shown to increase in averages by
1.62% under RCP 4.5 and by 1.96% for RCP 8.5 relative to the 1177.1mm of the baseline
period (1971-2000).
The results also showed that, temperature will slightly increase relative to the baseline
during present century (2011-2040) for RCP 4.5 and RCP 8.5. The ensemble average
project that the minimum temperature will increase by 14% (1.9 0 C) under RCP 8.5 and
maximum temperature by 7.68% (1.8 o C) under RCP 4.5
The findings of the third objective showed that there were significant changes in land use
and cover for the three-time periods (1990, 2006 and 2017). The cultivated land and built
up area increased from 25.69% in 1990 to 31.53% in 2006 and 43.57% in 2017 compared
to other land classes. Increase of cultivated land and built up area led to decrease in forest
cover. Forests occupied 7.54% in 1990, but decreased to 5.51% in 2006 and 5.23% in
2017. This decrease in forest cover has resulted in increased surface runoff for the same periods (2006-2017). The increase in surface runoff in the study area could be attributed
to deforestation and poor land husbandry, where during land preparation much of the
vegetation is cleared, hence decreasing canopy interception and allowing water to drain
off. Also, poor farming practices including cultivation on hillslopes without soil
conservation, reducing soil compaction, hence allowing more water to drain as surface
runoff.
The calibrated SWAT model using the three different land use and land cover change of
1990, 2006 and 2017 indicate that during the wet season, the mean monthly flow
increased by 1.48% relative to the 28.09 m 3 /s of the baseline 1990 while during the dry
season, the mean monthly flow decreased by 16.7% relative to the 0.20 m 3 /s baseline
flow. Assessment of the impacts of land use and land cover changes on catchment water
balance component revealed that surface runoff increased by 3.9% in 2006 and 9.01% in
2017 while groundwater contribution to stream flow decreased by 6.3% and 12.86% in
2006 and 2017, respectively. The decrease in stream flow could also be attributed to
abstraction of water for irrigation activities upstream of the Igawa gauge station.
The findings of the study may help basin water officers, planners in water sector and
agriculture sector in addressing uncertainty in policy and decision-making specifically
when preparing strategies and adaptations plans for river catchment. The science used in
this study can be applicable to another river basin in Tanzanian in a climate change
impact study.